Open Source Python Software
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Python Software
Browse free open source Python Software and projects below. Use the toggles on the left to filter open source Python Software by OS, license, language, programming language, and project status.
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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A cross-platform, open-source, alternative to NIST REFPROP. Based on reference-accuracy equations of state and transport property correlations for refrigerants like Water, CO2, R134a, Nitrogen, Argon, Ammonia, Air, R404a, R410a, Propane and many others. A selection of secondary working fluid properties are also available. Can also make use of REFPROP when available. In addition, calculations for Humid Air Properties based on ASHRAE RP-1485 are provided. Wrappers are available for MATLAB, Octave, Python, C#, Fortran and many more.
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Crossfire RPG game
Cooperative multiplayer graphical RPG and adventure game
Crossfire is a free, open-source, cooperative multi-player RPG and adventure game. Since its initial release, Crossfire has grown to encompass over 150 monsters, 3000 areas to explore, an elaborate magic system, 14 races, 16 character classes, and many powerful artifacts scattered far and wide. Set in a fantastical medieval world, it blends the style of Gauntlet, NetHack, Moria, and Angband. -
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GT New Horizons Mod Pack
New Modpack with Gregtech, Thaumcraft and Witchery
You are looking at a big progressive kitchensink pack for Minecraft 1.7.10 balanced around the mod GregTech. Over 9 years of development (and still going) have formed a balance and refinement that only a handful of packs can keep up with. We are talking about thousands of recipe tweaks, a massive questbook with over 3000 quests, unique world generation, custom mods coded for the pack, custom Thaumonomicon pages, and many more. The main intentions of the pack are a long-lasting experience and tying mods together in a progressive fashion, making it feel more like a single game than a compilation of mods thrown together. To reach this goal, GT New Horizons is using the tiers (basically ages of technology) from GregTech and allocates the content of other mods to a fitting point within the progression. Starting in the Stone Age you will barely be able to survive until you get your first steam machines and, eventually, reach electricity. -
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PortableApps.com
Portable software for cloud, local, and portable USB drives
PortableApps.com is the world's most popular portable software solution allowing you to take your favorite software with you. A fully open source and free platform, it works from any synced cloud folder (DropBox, Google Drive, Box, etc), from your local PC on an internal or external drive, or on any portable storage device (USB flash drive, memory card, portable SSD or hard drive, etc) moved between PCs. With millions of users all over the world, nearly 500 real open source and freeware apps in our main app store (no shovelware), compatible commercial software, and partners in hardware industry, PortableApps.com is the most complete solution for life on the go. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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leafmap
A Python package for interactive mapping and geospatial analysis
A Python package for geospatial analysis and interactive mapping in a Jupyter environment. Leafmap is a Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment. It is a spin-off project of the geemap Python package, which was designed specifically to work with Google Earth Engine (GEE). However, not everyone in the geospatial community has access to the GEE cloud computing platform. Leafmap is designed to fill this gap for non-GEE users. It is a free and open-source Python package that enables users to analyze and visualize geospatial data with minimal coding in a Jupyter environment, such as Google Colab, Jupyter Notebook, and JupyterLab. Leafmap is built upon several open-source packages, such as folium and ipyleaflet (for creating interactive maps), WhiteboxTools and whiteboxgui (for analyzing geospatial data), and ipywidgets (for designing interactive graphical user interface [GUI]). -
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RAGFlow
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data. -
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LangGraph
Build resilient language agents as graphs
LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application, crucial for creating reliable agents. Additionally, LangGraph includes built-in persistence, enabling advanced human-in-the-loop and memory features. -
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AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. This project is licensed under the Apache-2.0 License. Ensure you have access to an AWS account i.e. setup your environment such that awscli can access your account via either an IAM user or an IAM role. -
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Hermes Web UI
The best way to use Hermes Agent from the web or from your phone
Hermes WebUI is a browser-based interface for interacting with the Hermes autonomous agent, providing full feature parity with its command-line experience. It offers a clean, multi-panel layout that includes chat interaction, session management, and workspace file browsing. The interface allows users to manage agent sessions, configure models, and interact with persistent memory systems directly from a web environment. It is built using simple technologies like Python and vanilla JavaScript, avoiding complex frontend frameworks. The UI supports real-time interaction, context tracking, and visualization of token usage. It connects to a self-hosted agent that continuously learns and evolves over time. The project emphasizes usability, accessibility, and seamless integration with existing workflows. -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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Testcontainers Python
Testcontainers is a Python library that providing a friendly API
Testcontainers is a Python library that provides a friendly API to run a Docker container. It is designed to create a runtime environment to use during your automatic tests. -
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EverMemOS
Long-term memory OS for AI with structured recall and context awarenes
EverMemOS is an open-source memory operating system built to give AI agents long-term, structured memory. It captures conversations, transforms them into organized memory units, and enables agents to recall past interactions with context and meaning. Instead of treating each prompt independently, it builds evolving user profiles, tracks preferences, and connects related events into coherent narratives. Its architecture combines memory storage, indexing, and retrieval with agent-level reasoning, allowing AI systems to make informed decisions based on prior interactions. EverMemOS goes beyond simple retrieval by actively applying stored knowledge to current tasks, improving personalization and consistency. EverMemOS uses a multi-stage memory lifecycle to convert raw dialogue into structured semantic data, supporting long-horizon reasoning and adaptive behavior across sessions. -
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ACI.dev
Open platform connecting AI agents to tools via unified MCP server
ACI is an open source platform designed to enable AI agents to interact with external tools through a unified and structured interface. It focuses on simplifying tool integration by connecting hundreds of pre-built services into agentic environments, allowing developers to avoid building custom API clients and authentication flows for each service. ACI provides intent-aware tool access, meaning agents can dynamically discover and use tools based on context rather than rigid configurations. It supports both direct function calling and a unified Model Context Protocol (MCP) server, offering flexibility in how integrations are exposed to AI systems. ACI also includes multi-tenant authentication and permission controls, ensuring that tool usage is secure and scoped appropriately for different users and agents. Additionally, it is framework-agnostic, making it compatible with various large language model setups and agent architectures. -
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Microsandbox
Secure local-first microVM sandbox for running untrusted code fast
Microsandbox is an open source platform designed to securely execute untrusted code in isolated environments using lightweight virtualization techniques. It focuses on combining strong security guarantees with fast startup times by leveraging hardware-level microVM isolation instead of relying solely on traditional containers or full virtual machines. It aims to solve the common tradeoffs between speed, isolation, and control that developers encounter when running untrusted workloads. It provides a local-first and self-hosted approach, allowing users to maintain full ownership of their execution environment without depending on external cloud services. Microsandbox is particularly geared toward AI agent workflows, offering integrations that enable automated systems to safely run generated code and commands. It also supports standard container images, making it compatible with existing development ecosystems and tooling. -
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SQLFlow
SQL compiler bridging databases and machine learning workflows
SQLFlow is an open source project designed to bridge the gap between traditional SQL-based data processing and modern machine learning workflows by extending SQL syntax with AI capabilities. It acts as a compiler that translates SQL programs into executable workflows, enabling users to train, evaluate, and deploy machine learning models directly from SQL statements. It integrates with multiple database engines such as MySQL, Hive, and MaxCompute, while also supporting machine learning frameworks like TensorFlow and XGBoost. By embedding machine learning operations into SQL, it removes the need for users to switch between programming languages such as Python or R, simplifying the overall workflow. SQLFlow also supports model training, prediction, and explanation tasks, allowing data practitioners to work entirely within a familiar query interface. -
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Open SWE
Open source async coding agent that plans, codes, and opens PRs
Open SWE is an open source asynchronous coding agent designed to automate software engineering workflows across entire repositories. Built with LangGraph, it can understand a codebase, generate a structured plan, and execute code changes from start to finish without constant human intervention. It operates in a cloud-based environment where tasks are processed asynchronously, allowing multiple coding jobs to run in parallel in isolated sandboxes. It integrates directly with development workflows by responding to triggers from tools like GitHub, enabling users to initiate tasks through issues or comments. Open SWE is capable of creating commits and automatically opening pull requests once implementation is complete, effectively closing the loop on development tasks. It also supports interactive feedback during execution, allowing users to guide or adjust the process mid-task. Despite its advanced capabilities, the project has been officially marked as deprecated. -
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LaVague
Framework for building AI agents that automate complex web tasks
LaVague is an open source framework designed to help developers build AI-powered web agents capable of automating tasks across websites and web applications. It implements the concept of a Large Action Model framework, allowing agents to interpret a user-provided objective and translate it into a sequence of actions performed in a browser. These agents can navigate web pages, retrieve information, fill out forms, and execute multi-step workflows automatically. LaVague is centered around a World Model that analyzes the current webpage state and determines the next set of instructions, combined with an Action Engine that converts those instructions into executable automation code. It can use browser automation tools such as Selenium or Playwright to interact with websites programmatically. Developers can integrate various language models and configure the agent’s reasoning and execution behavior to suit different automation scenarios. -
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OptiMate
Libraries for optimizing AI models, inference speed, and GPU usage
Optimate is an open source collection of libraries designed to optimize the performance and cost efficiency of artificial intelligence models across different stages of the machine learning lifecycle. It groups several internal optimization tools developed by Nebuly AI into a single repository that focuses on improving inference speed, reducing infrastructure usage, and streamlining model training workflows. Its modules help developers automatically apply optimization techniques that better align AI models with the capabilities of the underlying hardware such as GPUs and CPUs. One of the core components, Speedster, focuses on accelerating model inference by applying state of the art optimization techniques to increase performance while lowering operational costs. Another component, Nos, targets infrastructure optimization by improving GPU utilization in Kubernetes clusters through dynamic partitioning and elastic resource quotas. -
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Memori
SQL-native memory layer enabling persistent context for AI agents
Memori is an open source SQL-native memory engine designed to add persistent memory capabilities to AI applications, large language models, and multi-agent systems. It provides a memory layer that automatically captures conversations and interactions between users and AI models, allowing systems to retain knowledge across sessions instead of operating statelessly. It extracts structured information such as facts, preferences, rules, and summaries from interactions and stores them in standard SQL databases for later retrieval. By recalling relevant context during future model calls, Memori helps AI agents produce more consistent and context-aware responses while reducing the need to repeatedly provide background information. Memori is designed to work with multiple LLM providers, data stores, and AI frameworks, allowing it to integrate into existing software architectures without requiring major changes. -
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FinalRecon
All-in-one Python web reconnaissance tool for fast target analysis
FinalRecon is an all-in-one web reconnaissance tool written in Python that helps security professionals gather information about a target website quickly and efficiently. It combines multiple reconnaissance techniques into a single command-line utility so users do not need to run several separate tools to collect similar data. FinalRecon focuses on providing a fast overview of a web target while maintaining accuracy in the collected results. It includes modules for gathering server information, analyzing SSL certificates, performing WHOIS lookups, and crawling website resources. FinalRecon can also enumerate DNS records, discover subdomains, search for directories and files, and scan common network ports. Historical URLs and resources can be retrieved from archived sources to help analyze changes in a website over time. Designed primarily for penetration testers and security researchers, FinalRecon simplifies the reconnaissance phase of security assessments. -
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User Scanner
Scan usernames and emails across many platforms from the CLI
user-scanner is a command-line OSINT tool designed to analyze the presence and availability of usernames and email addresses across many online platforms. It helps users quickly determine whether a specific username or email is already associated with accounts on social networks, developer platforms, creator communities, gaming services, and other sites. user-scanner is useful for security researchers, investigators, and analysts performing open source intelligence, as well as individuals or businesses looking for a unique username across multiple services. By scanning many platforms in a single command, it simplifies the process of checking account existence and identifying a digital footprint. user-scanner uses a modular architecture where each platform is implemented as a small validator module that determines whether a username exists or is available. -
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Kirstens Viewers
Opensource Created Custom Viewers For Virtual Worlds like SecondLife.
Kirsten’s Viewer is a fast, modern Third‑Party Viewer (TPV) for Second Life, registered under the official TPV directory. It’s built for creators, photographers, and advanced users who want a clean, modern viewer with a focus on high performance on high end PC's Anaglyph 3D Mode , OpenCL‑based Visual Effects, Aggressive Optimisation, vcpkg + PowerShell One‑Click Build Automation, Highly Tuned Graphics Path , Many Other Cutting‑Edge Features — ongoing experimental work, performance improvements, and creator‑driven enhancements continue to push the viewer forward. -
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Arize Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
Phoenix provides ML insights at lightning speed with zero-config observability for model drift, performance, and data quality. Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative) are an amazing technology that will power many of future ML use cases. A large set of these technologies are being deployed into businesses (the real world) in what we consider a production setting. -
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This program is a password generator. It uses a hashing algorithm to transform a master password into unique and complex site or service specific passwords. It's written in Python and runs either in GUI mode (using GTK+) or in text console.
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Memobase
Fast backend for long-term AI user memory via structured profiles
Memobase is an open source backend system that enables long-term user memory functionality for AI applications by capturing and structuring information about users across interactions. Its design centers on creating user profiles and recording event timelines, allowing AI systems to remember, understand, and evolve in their behaviour toward individual users over time. Instead of relying purely on traditional embedding-based retrieval or RAG systems, Memobase uses profile and timeline structures to deliver memory that reflects user context efficiently and meaningfully. The system focuses on three principal performance metrics: high search performance, reduced large language model (LLM) costs through batch processing techniques, and low latency with minimal SQL operations. Memobase supports integration with existing LLM workflows via APIs and SDKs (including Python, Node, and Go), making it easy to adopt within diverse application stacks. -
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Shaderc
A collection of tools, libraries, and tests for Vulkan shader
Shaderc is a collection of tools and libraries for compiling shaders—small programs that run on GPUs—into SPIR-V, the intermediate representation used by the Vulkan graphics API. It provides both a command-line tool (glslc) and a C/C++ library (libshaderc) that wrap the functionality of glslang (the Khronos reference compiler for GLSL) and SPIRV-Tools to deliver a modern, scriptable, and efficient shader compilation workflow. The glslc compiler offers a GCC/Clang-like interface for building GLSL and HLSL shaders, making it easy to integrate into existing build systems. Meanwhile, libshaderc exposes a stable API that allows developers to programmatically compile shader strings into SPIR-V modules within graphics engines and tools. Shaderc supports advanced features such as file inclusion (#include), concurrency, and cross-platform builds, and it maintains backward compatibility for long-term projects.
